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Developing a Social Determinants of Health Common Data Model for
PRAPARE (Protocol for Responding to and Assessing Patient Assets, Risks,
and Experiences)
Session 213, February 14, 2019
Andrew Hamilton, Chief Informatics Officer, AllianceChicago
Rosy Chang Weir, Director of Research, Association of Asian Pacific Community Health Organizations
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Andrew Hamilton, RN, BSN, MS
Rosy Chang Weir, PhD
Have no real or apparent conflicts of interest to report.
Conflict of Interest
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Learning Objectives
• Describe the process for creating a CHC common data model
including SDOH data elements
• Discuss how a CHC common data model will be used to improve
the representation of under-represented communities in health
services research
• Discuss aspects of the proposed data model, including key value-
sets related to social and economic risk factor data and how those
data elements related to existing/emerging common data models
• Describe the PRAPARE protocol and the importance of
standardized collection of SDOH data
• Discuss how the PRAPARE data model relates to other tools
utilized to collect social and economic risk factor data
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Bay Area regional Health Inequities Initiative (BARHII). 2008. “Health Inequities in the Bay Area”, accessed November 28, 2012 from
http://barhii.org/resources/index.html.
Why Collect Data on Social Determinants of
Health (SDH)?
How well
do we
know our
patients?
Are services
addressing
SDH
reimbursed
and/or
sustainable?
Are
community
partnerships
adequate and
integrated?
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What is PRAPARE?
Protocol for Responding to & Assessing
Patients’ Assets, Risks & Experiences:
A national standardized patient risk assessment protocol
designed to engage patients in assessing & addressing social
determinants of health (SDH).
PRAPARE = SDH screening tool + implementation/action
process
Created by: National Association of Community Health Centers,
Association of Asian Pacific Community Health Organizations, Oregon
Primary Care Association, Institute for Alternative Futures in partnership
with others, including AllianceChicago
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Community Health Centers Today
Largest national network of primary/preventive
care
•27+ million patients at 10,400+ sites
• 1 in 12 US residents
• 1 in 6 Medicaid beneficiaries
• 1 in 3 low income, uninsured
• 1 in 3 people in poverty
• 1 in 3 racial/ethnic minority individuals in
poverty
• 1.3 million homeless persons
• 965,000+ migrant farmworkers
1400 Health Center Orgs.
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Health Center Model of Care
• Community governance
• Located in/serve federally-designated medically underserved
areas
• Non-profit, must be open to all
• Comprehensive health services
– Care team, care integration, community partners
– “Enabling” and social services
• Community needs assessments
• Strict performance/accountability standards
– Quality Improvement/Assurance Plans
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• FREE EHR Templates Available*:
– NextGen
– eClinical Works
– GE Centricity
– Epic
– Cerner*
– Greenway Intergy
– Meditab
Available for FREE after signing EULA
at www.nachc.org/prapare
• In development:
– Greenway Success
EHS
– Allscripts
– Athena
– Meditech
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PRAPARE EHR Templates
70% of all health
centers
Current 7 + New EHRs =
85-95% of all health centers
* Automatically map to ICD-10 Z codes so you can easily add relevant Z codes to problem or diagnostic list
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PRAPARE Domains
Publication pending. Do not quote or
distribute without permission from NACHC.
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PRAPARE’s Unique Design
• STANDARDIZED and WIDELY USED
– Measures Linked with standardized codes
• EVIDENCE-BASED and STAKEHOLDER-DRIVEN
• FREE EHR Templates: eClinicalWorks, Epic, NextGen, GE
Centricity, +
• FREE PRAPARE Implementation and Action
Resources
• WORKFLOW AGNOSTIC
– Can fit within existing workflows and be combined with
other tools/data
• PATIENT-CENTERED and ACTIONABLE
– Actionable at patient and population level
– Meant to facilitate conversations and build relationships with
patients
– Standardize the need rather than the question
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Pilot Results (2015 and 2017)
• Easy to administer
• Possible to implement using various workflows and
staffing models
• Builds patient-provider relationship
• Identifies new needs
• Leads to positive changes at the patient, health center,
and community/population levels
• Facilitates collaboration with community partners
• Importance of targeted messaging and staff support
Publication pending. Do not quote or
distribute without permission from NACHC.
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0%
5%
10%
15%
20%
25%
30%
35%
0 1 2 3 4 5 6 7 8 9 10111213141516171819202122
Tally Score
Alliance/Iowa Waianae New York Oregon Total
3 CHCs
1 CHC
2 CHCs 1 CHC
7 CHCs
Percent of Patients with Number* of SDH “Tallies”
N = 2,694 patients for all teams
* Excludes
low income
This health center pilot
population had highest burden
of chronic illness.
Publication pending. Do
not quote or distribute
without permission from
NACHC.
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Positive Correlation Between SDH
Factors* and Hypertension: All Teams
0%
10%
20%
30%
40%
50%
0 1 2 3 4 5 6 7 8 9 1011121314151617
Tally Score
% of POF % of the tally score with Hypertension
r = 0.61
*Excludes low income
Publication pending. Do not quote or
distribute without permission from NACHC.
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BOTH are necessary to:
• Demonstrate value to payers
• Advocate for upstream investments
• Seek adequate financing to ensure interventions are sustainable
• Achieve integrated, value-driven delivery system and reduce total cost
of care
Importance of Social Determinants
Intervention & Enabling Services Data
NEED DATA
• Standardized
data on patient
social risk
/barriers
(PRAPARE)
RESPONSE DATA
• Standardized data
on interventions
(Enabling Services +
others)
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Examples of Using PRAPARE Data
• Patient-level improvements:
– Matching Rx and Tx plans to patient circumstances
– In-house and community assistance programs
• Organizational and Community level actions
– Expand enabling services
– Mobile outreach
– Prioritize development of community partnerships
– Referral resource guides and referral networks
– Risk segmentation and stratification
• System level
– Payer and delivery system partner engagement
– Alternative payment methodologies
Publication pending. Do not
quote or distribute without
permission from NACHC.
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Inform Care and Services:
Inform services provided in Collaborative
Consortia Model and Co-Location Model
Build/strengthen partnerships with local
orgs. Ex: Negotiate bulk discounts and new
bus routes with local transportation agency
Build on SDH and “Touches” work
Inform Payment
Guide work of co-located foundation to pay
for non-clinical services
Inform both
Medicaid and
Medicare ACO
discussions and
care management
policies
Inform payment
reform discussions
with state Medicaid
agency
Inform Risk
Adjustment
Create SDH risk
score for risk
stratification and
risk adjustment
Streamline and expand care management
plans
Assign weights: Put
every PRAPARE
element in
regression model
with certain
outcome or cost
Inform APM
discussions at
state level
Ways to Use PRAPARE Data
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PRAPARE-Interventions/ES
Conceptual framework
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Appropriate Care
(e.g., HbA1c test, preventive
vaccinations)
Health Outcomes
(e.g., HbA1c level, ED
visits)
Enabling Services & other non-clinical SDH interventions
Social Determinants of
Health
(PRAPARE)
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Example of Risk Stratification
Using PRAPARE Data
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• 1,000+ downloaded a PRAPARE EHR template, but
reach is higher
• Not just health centers
– Hospitals, health systems, ACOs, payers, population
health vendors
• State-based spread activities
• Happy to work with new vendors and partners!
– Please reach out to NACHC before you get started
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PRAPARE Reach as of Jan 2018
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Key Challenges in Standardizing Data
on Patient Social Risks
• Growing awareness of the impact of social and economic
factors impacting health has lead to development of several
screening tools & innovative clinical interventions
• Scaling the screening and clinical intervention efforts remains
difficult:
– Lack of existing data and data value sets to accelerate
interoperability
– Misaligned incentives (fee for medical service)
– Healthcare workforce competent in addresses social care
needs
– Fragmentation of clinical and social care services
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Also includes neighborhood and optional questions (incarceration history, refugee status,
safety, domestic violence).
SDOH Data Elements in National Data Programs
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HIT Vendor Response by Type
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Vendor Practices
Freij M, Dullabh P, Hovey L, Leonard J, Card A, Dhopeshwarkar R. Incorporating
Social Determinants of Health in Electronic Health Records: A Qualitative Study of
Perspectives on Current Practices among Top Vendors. Washington, DC: U.S.
Department of Health and Human Services Office of Health Policy; 2018.
Motivation to Support Collection of
SDOH Data
• Requests by Customers
• Data for Performance Improvement
• ONC Certification Requirements
Key Challenge:
• Lack of National Data Standards
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Value Sets
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• Summary of Care
• Population Health
• Health Information Exchange
• Data/Analytics & Predictive Model
• Research
Interoperability of SDH data
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After Visit Summary & Care Coordination
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Pop Health and SDH data
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Pop Health and SDH data
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Diabetes Screening: Traditional
Approach
* A project in partnership with the University of
Chicago Data Science for Social Good Program
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Predictive Analytics
SDH Data
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SDH Data in Predictive Models
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Predictive Model Outperforms USPSTF
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Distributed Research Network
Facilitate multisite research collaborations between
investors and data stewards by creating secure
networking capabilities and analysis tools
– Ability to work with analysis-ready datasets
– Standardized data using a common data model
– Data stewards keep and analyze their own data
– Provide results (not full set) of raw data to requestor
– All activities audited and secured
NIH Webinar: https://www.nihcollaboratory.org/Pages/distributed-research-
network.aspx
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• Strengthening Public Health through
National Partnerships
• 39 Funded Agencies including
NACHC
• CDC & NACHC Clinical Focus:
o Cardiac Disease
o Hepatitis B & C
o Family Planning
o Post-Partum Diabetes
o Adult Vaccination
CDC & NACHC: Essential Public Health Services
https://www.cdc.gov/publichealthgateway/partnerships/capacity-building-
assistance-OT18-1802.html
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HCV Care Cascade
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• Collecting SDH data in the healthcare setting is possible, however
requires thoughtful consideration in terms of workflow as well as
staff and patient education
• There are several SDH screening tools, however, data standards
are not fully defined, therefore interoperability of these data
continues to be a challenge
• HIT vendors are beginning to incorporate SDH data
• There are several use cases related to SDH data including point
of care, population health, decision support, research and public
health
• As SDH data standards are developed, existing shared data
models will need to be updated to include these data
Summary
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Acknowledging Our Funders
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Questions
Andrew Hamilton, RN, BSN, MS
Chief Informatics Officer/Deputy Director
AllianceChicago
312.267.2017
ahamilton@alliancechicago.org
Rosy Chang Weir, PhD
Director of Research
Association of Asian Pacific Community Health Organizations
510-272-9536
rcweir@aapcho.org
To sign up for the PRAPARE listserv, email prapare@nachc.org
